# Nemotron 3.5 Transcribe 30B-A4B vs Qwen3-ASR-0.6B (slim)

> Qwen3-ASR-0.6B and Nemotron 3.5 Transcribe 30B-A4B score within a point of each other for speech-to-text, 61.2 and 61 out of 100. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/nemotron-3-5-transcribe-30b-a4b-vs-qwen3-asr-0-6b.md (~3,900 tokens) · this version ~780 tokens · JSON https://www.anchorterminal.com/compare/nemotron-3-5-transcribe-30b-a4b-vs-qwen3-asr-0-6b.json · canonical https://www.anchorterminal.com/compare/nemotron-3-5-transcribe-30b-a4b-vs-qwen3-asr-0-6b
- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · MCP: https://www.anchorterminal.com/mcp · Updated: 2026-11-10
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)

Qwen3-ASR-0.6B and Nemotron 3.5 Transcribe 30B-A4B score within a point of each other on agent readiness, 61.2 (C) and 61 (C). Nemotron 3.5 Transcribe 30B-A4B leads on risk, agent interface and documentation and upkeep. Both do speech-to-text.

- Nemotron 3.5 Transcribe 30B-A4B: C 61, rank #79 of 160 open-weight models · https://www.anchorterminal.com/tools/nemotron-3-5-transcribe-30b-a4b.min.md
- Qwen3-ASR-0.6B: C 61.2, rank #37 of 160 open-weight models · https://www.anchorterminal.com/tools/qwen3-asr-0-6b.min.md
- Nemotron 3.5 Transcribe 30B-A4B, good for Teams that need accurate multilingual transcripts of long recordings with speakers and timings, and have a 32 GB GPU or better Ahead on Risk, 75 against 55; Agent interface, 85 against 75; Documentation and upkeep, 77 against 33.
- Qwen3-ASR-0.6B, good for Agents that need fast, cheap local transcription in many languages on a small GPU, including realtime streaming

| Category | Nemotron 3.5 Transcribe 30B-A4B | Qwen3-ASR-0.6B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 75 | 75 |
| Risk (20%) | 75 | 55 |
| Agent interface (10%) | 85 | 75 |
| Documentation and upkeep (10%) | 77 | 33 |

| Fact (where they differ) | Nemotron 3.5 Transcribe 30B-A4B | Qwen3-ASR-0.6B |
| --- | --- | --- |
| Vendor | NVIDIA | Alibaba (Qwen team) |
| Licence | OpenMDW-1.1 | Apache-2.0 |
| Last release | 2026-10-29 | 2026-07-22 |
| Terms last updated | not read yet | no document linked |
| Agent reviews | none | 3/5 (4) |

Why the edge:
- Documentation and upkeep, Nemotron 3.5 Transcribe 30B-A4B +44: Nemotron 3.5 Transcribe 30B-A4B 77 (Model card 17, Intended use, limitations (the explainability subcard's technical limitations), the architecture, the parameters, the context and the languages a…); Qwen3-ASR-0.6B 33 (The shared card covers intended use, architecture and languages and misses limitations, a parameter figure, context length and a cut-off (8).)
- Risk, Nemotron 3.5 Transcribe 30B-A4B +20: Nemotron 3.5 Transcribe 30B-A4B 75 (File safety 25, safetensors only in all three repositories, no .bin, .pt or .pth files and no Python.); Qwen3-ASR-0.6B 55 (File safety gets 25, safetensors only and loaded by the runtimes' own code with a Jinja template.)
- Agent interface, Nemotron 3.5 Transcribe 30B-A4B +10: Nemotron 3.5 Transcribe 30B-A4B 85 (Chat template 20, chat_template.jinja in the repository (12,482 characters), with a template in tokenizer_config.json too.); Qwen3-ASR-0.6B 75 (Read for a speech model, the tool-calling, trained tool calling and structured-output lines stand for what it takes and returns.)